In-house solution for the RecSys challenge 2015

Nadav Cohen, Bracha Shapira, Adi Gerzi, Lior Rokach, David Ben-Shimon, Michael Friedmann

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

RecSys Challenge 2015 is about predicting the items a user will buy in a given click session. We describe the in-house solution to the challenge as guided by the YOOCHOOSE team. The presented solution achieved 14th place in the challenge's final leaderboard with a score of 51,932 points, while the winner obtained 63,102 points. We suggest two simple and easy to reconstruct approaches for obtaining a prediction in each session. In the first approach we suggest one classifier to determine whether each item in the session will be bought. In the second approach we suggest a two level classification model in which the first level determines whether the session is going to end with a purchase or not, and if it ends with a purchase, the second level classification determines the items that are going to be purchased.

Original languageEnglish
Title of host publicationProceedings of the International ACM Recommender Systems Challenge 2015
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450336659
DOIs
StatePublished - 16 Sep 2015
EventInternational ACM Recommender Systems Challenge, RecSys 2015 - Vienna, Austria
Duration: 16 Sep 2015 → …

Publication series

NameProceedings of the International ACM Recommender Systems Challenge 2015

Conference

ConferenceInternational ACM Recommender Systems Challenge, RecSys 2015
Country/TerritoryAustria
CityVienna
Period16/09/15 → …

Keywords

  • In-house solution
  • RecSys challenge 2015
  • Recommender systems

Fingerprint

Dive into the research topics of 'In-house solution for the RecSys challenge 2015'. Together they form a unique fingerprint.

Cite this